RNA sequencing analysis to capture the transcriptome landscape during skin ulceration syndrome progression in sea cucumber Apostichopus japonicus

Abstract

Background: Sea cucumber Apostichopus japonicus is an important economic species in China, which is affected by various diseases; skin ulceration syndrome (SUS) is the most serious. In this study, we characterized the transcriptomes in A. japonicus challenged with Vibrio splendidus to elucidate the changes in gene expression throughout the three stages of SUS progression.

Results: RNA sequencing of 21 cDNA libraries from various tissues and developmental stages of SUS-affected A. japonicus yielded 553 million raw reads, of which 542 million high-quality reads were generated by deep-sequencing using the Illumina HiSeq™ 2000 platform. The reference transcriptome comprised a combination of the Illumina reads, 454 sequencing data and Sanger sequences obtained from the public database to generate 93,163 unigenes (average length, 1,052 bp; N50 = 1,575 bp); 33,860 were annotated. Transcriptome comparisons between healthy and SUS-affected A. japonicus revealed greater differences in gene expression profiles in the body walls (BW) than in the intestines (Int), respiratory trees (RT) and coelomocytes (C). Clustering of expression models revealed stable up-regulation as the main pattern occurring in the BW throughout the three stages of SUS progression. Significantly affected pathways were associated with signal transduction, immune system, cellular processes, development and metabolism. Ninety-two differentially expressed genes (DEGs) were divided into four functional categories: attachment/pathogen recognition (17), inflammatory reactions (38), oxidative stress response (7) and apoptosis (30). Using quantitative real-time PCR, twenty representative DEGs were selected to validate the sequencing results. The Pearson's correlation coefficient (R) of the 20 DEGs ranged from 0.811 to 0.999, which confirmed the consistency and accuracy between these two approaches.

Conclusions: Dynamic changes in global gene expression occur during SUS progression in A. japonicus. Elucidation of these changes is important in clarifying the molecular mechanisms associated with the development of SUS in sea cucumber.

Keywords: Dynamic expression profiles; RNA sequencing; Sea cucumber (Apostichopus japonicus); Skin ulceration syndrome.

Fig. 1

Features associated with each stage of SUS and indicators of the sampling positions. a Healthy A. japonicus. b and c SUS and its distal normal BW at stage I of SUS progression. d and e SUS and its distal normal BW at stage II of SUS progression. f and g SUS and its distal normal BW at stage III of SUS progression

Fig. 2

Dynamic expression patterns in A. japonicus during SUS progression. The expression profiles of the DEGs [the log₂Ratio ≥1 and the RPKM >2 at a minimum of one time-point] were determined over the three stages of SUS progression by clustering analysis based on the K-means method using the Euclidean distance algorithm. The three points along the x-axis represent I-SUS-BW/H-BW, II-SUS-BW/H-BW and III-SUS-BW/H-BW. Each tick on the y-axis represents a value of 1. Midline represents 0. “+1” represents up-regulated expression. “-1” represents down-regulated expression

Fig. 3

Significantly enriched pathway among the DEGs revealed by the up-regulated expression models in A. japonicus during SUS progression. Blue: Pathways related to signal transduction. Magenta: Pathways related to the immune system. Red: Pathways related to cellular processes. Green: Pathways related to development. Orange: Pathways related to metabolism. Pink: Pathways related to genetic information processing

Fig. 4

Validation of RNA-seq results using qRT-PCR. Twenty DEGs were selected and their relative fold changes were expressed as the ratio of gene expression in BW of A. japonicus at SUS stages I, II and III compared to H samples as normalized with the Cytb gene. The data obtained from the first RNA-seq and qRT-PCR were compared correspondingly and drawn as a Pearson correlation scatter plot